Mirtazapine and paroxetine: a drug-drug interaction study in healthy subjects

Direct and quantitative evaluation of the major human CYP contribution (fmCYP) to drug clearance using the in vitro Silensomes™ model

1. We have applied the concept of using MBIs to produce CYP-Silensomes to quantify the contribution of the major CYPs to drug metabolism (fmCYP). 2. The target CYPs were extensively and selectivity inhibited by the selected MBIs, while non-target CYPs were inhibited by less than 20% of the homologous control activities. Only CYP2D6-Silensomes exhibited a CYP2B6 inhibition that could be easily and efficiently encountered by subtracting the fm_CYP2B6 measured using CYP2B6-Silensomes to adjust the fm_CYP2D6. 3. To validate the use of a panel of 6 CYP-Silensomes, we showed that the fmCYP values of mono- and multi-CYP metabolised drugs were well predicted, with 70% within ± 15% accuracy. Moreover, the correlation with observed fmCYP values was higher than that for rhCYPs, which were run in parallel using the same drugs (<45% within ±15% accuracy). Moreover, the choice of the RAF substrate in rhCYP predictions was shown to affect the accuracy of the fmCYP measurement. 4. These results support the use of CYP1A2-, CYP2B6-, CYP2C8-, CYP2C9-, CYP2D6 and CYP3A4-Silensomes to accurately predict fmCYP values during the in vitro enzyme phenotyping assays in early, as well as in development, phases of drug development.

Inhibitory metabolic drug interactions with newer psychotropic drugs: inclusion in package inserts and influences of concurrence in drug interaction screening software

BACKGROUND

Food and Drug Administration (FDA) regulations mandate that package inserts (PIs) include observed or predicted clinically significant drug-drug interactions (DDIs), as well as the results of pharmacokinetic studies that establish the absence of effect.

OBJECTIVE

To quantify how frequently observed metabolic inhibition DDIs affecting US-marketed psychotropics are present in FDA-approved PIs and what influence the source of DDI information has on agreement between 3 DDI screening programs.

METHODS

The scientific literature and PIs were reviewed to determine all drug pairs for which there was rigorous evidence of a metabolic inhibition interaction or noninteraction. The DDIs were tabulated noting the source of evidence and the strength of agreement over chance. Descriptive statistics were used to examine the influence of source of DDI information on agreement among 3 DDI screening tools. Logistic regression was used to assess the influence of drug class, indication, generic status, regulatory approval date, and magnitude of effect on agreement between the literature and PI as well as agreement among the DDI screening tools.

RESULTS

Thirty percent (13/44) of the metabolic inhibition DDIs affecting newer psychotropics were not mentioned in PIs. Drug class, indication, regulatory approval date, generic status, or magnitude of effect did not appear to be associated with more complete DDI information in PIs. DDIs found exclusively in PIs were 3.25 times more likely to be agreed upon by all 3 DDI screening tools than were those found exclusively in the literature. Generic status was inversely associated with agreement among the DDI screening tools (odds ratio 0.11; 95% CI 0.01 to 0.89).

CONCLUSIONS

The presence in PIs of DDI information for newer psychotropics appears to have a strong influence on agreement among DDI screening tools. Users of DDI screening software should consult more than 1 source when considering interactions involving generic psychotropics.

Age-related changes in antidepressant pharmacokinetics and potential drug-drug interactions: a comparison of evidence-based literature and package insert information

BACKGROUND

Antidepressants are among the most commonly prescribed psychotropic agents for older patients. Little is known about the best source of pharmacotherapy information to consult about key factors necessary to safely prescribe these medications to older patients.

OBJECTIVE

The objective of this study was to synthesize and contrast information in the package insert (PI) with information found in the scientific literature about age-related changes of antidepressants in systemic clearance and potential pharmacokinetic drug-drug interactions (DDIs).

METHODS

A comprehensive search of two databases (MEDLINE and EMBASE from January 1, 1975 to September 30, 2011) with the use of a combination of search terms (antidepressants, pharmacokinetics, and drug interactions) was conducted to identify relevant English language articles. This information was independently reviewed by two researchers and synthesized into tables. These same two researchers examined the most up-to-date PIs for the 26 agents available at the time of the study to abstract quantitative information about age-related decline in systemic clearance and potential DDIs. The agreement between the two information sources was tested with κ statistics.

RESULTS

The literature reported age-related clearance changes for 13 antidepressants, whereas the PIs only had evidence about 4 antidepressants (κ < 0.4). Similarly, the literature identified 45 medications that could potentially interact with a specific antidepressant, whereas the PIs only provided evidence about 12 potential medication-antidepressant DDIs (κ < 0.4).

CONCLUSION

The evidence-based literature compared with PIs is the most complete pharmacotherapy information source about both age-related clearance changes and pharmacokinetic DDIs with antidepressants. Future rigorously designed observational studies are needed to examine the combined risk of antidepressants with age-related decline in clearance and potential DDIs on important health outcomes such as falls and fractures in older patients.

Clinically significant drug interactions with newer antidepressants

After the introduction of selective serotonin reuptake inhibitors (SSRIs), other newer antidepressants with different mechanisms of action have been introduced in clinical practice. Because antidepressants are commonly prescribed in combination with other medications used to treat co-morbid psychiatric or somatic disorders, they are likely to be involved in clinically significant drug interactions. This review examines the drug interaction profiles of the following newer antidepressants: escitalopram, venlafaxine, desvenlafaxine, duloxetine, milnacipran, mirtazapine, reboxetine, bupropion, agomelatine and vilazodone. In general, by virtue of a more selective mechanism of action and receptor profile, newer antidepressants carry a relatively low risk for pharmacodynamic drug interactions, at least as compared with first-generation antidepressants, i.e. monoamine oxidase inhibitors (MAOIs) and tricyclic antidepressants (TCAs). On the other hand, they are susceptible to pharmacokinetic drug interactions. All new antidepressants are extensively metabolized in the liver by cytochrome P450 (CYP) isoenzymes, and therefore may be the target of metabolically based drug interactions. Concomitant administration of inhibitors or inducers of the CYP isoenzymes involved in the biotransformation of specific antidepressants may cause changes in their plasma concentrations. However, due to their relatively wide margin of safety, the consequences of such kinetic modifications are usually not clinically relevant. Conversely, some newer antidepressants may cause pharmacokinetic interactions through their ability to inhibit specific CYPs. With regard to this, duloxetine and bupropion are moderate inhibitors of CYP2D6. Therefore, potentially harmful drug interactions may occur when they are coadministered with substrates of these isoforms, especially compounds with a narrow therapeutic index. The other new antidepressants are only weak inhibitors or are not inhibitors of CYP isoforms at usual therapeutic concentrations and are not expected to affect the disposition of concomitantly administered medications. Although drug interactions with newer antidepressants are potentially, but rarely, clinically significant, the use of antidepressants with a more favourable drug interaction profile is advisable. Knowledge of the interaction potential of individual antidepressants is essential for safe prescribing and may help clinicians to predict and eventually avoid certain drug combinations.

Quantitative prediction of cytochrome P450 (CYP) 2D6-mediated drug interactions

BACKGROUND AND OBJECTIVES

An approach was recently proposed for quantitative predictions of cytochrome P450 (CYP) 3A4-mediated drug-drug interactions. This approach relies solely on in vivo data. It is based on two characteristic parameters: the contribution ratio (CR; i.e. the fraction of victim drug clearance due to metabolism by a specific CYP) and the inhibition ratio (IR) of the inhibitor. Knowledge of these parameters allows forecasting of the ratio between the area under the plasma concentration-time curve (AUC) of the victim drug when the inhibitor is co-administered and the AUC of the victim drug administered alone. The goals of our study were to extend this method to CYP2D6-mediated interactions, to validate it, and to forecast the magnitude of a large number of interactions that have not been studied so far.

METHODS

A three-step approach was pursued. First, initial estimates of CRs and IRs were obtained by several methods, using data from the literature. Second, an external validation of these initial estimates was carried out, by comparing the predicted AUC ratios with the observed values. Third, refined estimates of CRs and IRs were obtained by orthogonal regression in a Bayesian framework.

RESULTS

Thirty-nine AUC ratios were available for external validation. The mean prediction error of the ratios was 0.31, while the mean prediction absolute error was 1.14. Seventy AUC ratios were available for the global analysis. Final estimates of CRs and IRs were obtained for 39 substrates and 11 inhibitors, respectively. The mean prediction error of the AUC ratios was 0.04, while the mean prediction absolute error was 0.51.

CONCLUSIONS

Predictive distributions for 615 possible interactions were obtained, giving detailed information on some drugs or inhibitors that have been poorly studied so far, such as metoclopramide, bupropion and terbinafine.

Getting the balance right: Established and emerging therapies for major depressive disorders

Major depressive disorder (MDD) is a common and serious illness of our times, associated with monoamine deficiency in the brain. Moreover, increased levels of cortisol, possibly caused by stress, may be related to depression. In the treatment of MDD, the use of older antidepressants such as monoamine oxidase inhibitors and tricyclic antidepressants is decreasing rapidly, mainly due to their adverse effect profiles. In contrast, the use of serotonin reuptake inhibitors and newer antidepressants, which have dual modes of action such as inhibition of the serotonin and noradrenaline or dopamine reuptake, is increasing. Novel antidepressants have additive modes of action such as agomelatine, a potent agonist of melatonin receptors. Drugs in development for treatment of MDD include triple reuptake inhibitors, dual-acting serotonin reuptake inhibitors and histamine antagonists, and many more. Newer antidepressants have similar efficacy and in general good tolerability profiles. Nevertheless, compliance with treatment for MDD is poor and may contribute to treatment failure. Despite the broad spectrum of available antidepressants, there are still at least 30% of depressive patients who do not benefit from treatment. Therefore, new approaches in drug development are necessary and, according to current research developments, the future of antidepressant treatment may be promising.

Mirtazapine: a review of its use in major depression and other psychiatric disorders

Mirtazapine (Remeron, Zispin) is a noradrenergic and specific serotonergic antidepressant (NaSSA) that is approved in many counties for use in the treatment of major depression. Monotherapy with mirtazapine 15-45 mg/day leads to rapid and sustained improvements in depressive symptoms in patients with major depression, including the elderly. It is as effective as other antidepressants and may have a more rapid onset of action than selective serotonin reuptake inhibitors (SSRIs). Furthermore, it may also have a higher sustained remission rate than amitriptyline. Preliminary data suggest that mirtazapine may also be effective in the treatment of anxiety disorders (including post-traumatic stress disorder, panic disorder and social anxiety disorder), obsessive-compulsive disorder, undifferentiated somatoform disorder and, as add-on therapy, in schizophrenia, although large, well designed trials are needed to confirm these findings. Mirtazapine is generally well tolerated in patients with depression. In conclusion, mirtazapine is an effective antidepressant for the treatment of major depression and also has the potential to be of use in other psychiatric indications.

Clinically relevant pharmacokinetic drug interactions with second-generation antidepressants: an update

BACKGROUND

The second-generation antidepressants include selective serotonin reuptake inhibitors (SSRIs), serotonin and norepinephrine reuptake inhibitors (SNRIs), and other compounds with different mechanisms of action. All second-generation antidepressants are metabolized in the liver by the cytochrome P450 (CYP) enzyme system. Concomitant intake of inhibitors or inducers of the CYP isozymes involved in the biotransformation of specific antidepressants may alter plasma concentrations of these agents, although this effect is unlikely to be associated with clinically relevant interactions. Rather, concern about drug interactions with second-generation antidepressants is based on their in vitro potential to inhibit > or = 1 CYP isozyme.

OBJECTIVE

The goal of this article was to review the current literature on clinically relevant pharmacokinetic drug interactions with second-generation antidepressants.

METHODS

A search of MEDLINE and EMBASE was conducted for original research and review articles published in English between January 1985 and February 2008. Among the search terms were drug interactions, second-generation antidepressants, newer antidepressants, SSRIs, SNRIs, fluoxetine, paroxetine, fluvoxamine, sertraline, citalopram, escitalopram, venlafaxine, duloxetine, mirtazapine, reboxetine, bupropion, nefazodone, pharmacokinetics, drug metabolism, and cytochrome P450. Only articles published in peer-reviewed journals were included, and meeting abstracts were excluded. The reference lists of relevant articles were hand-searched for additional publications.

RESULTS

Second-generation antidepressants differ in their potential for pharmacokinetic drug interactions. Fluoxetine and paroxetine are potent inhibitors of CYP2D6, fluvoxamine markedly inhibits CYP1A2 and CYP2C19, and nefazodone is a substantial inhibitor of CYP3A4. Therefore, clinically relevant interactions may be expected when these antidepressants are coadministered with substrates of the pertinent isozymes, particularly those with a narrow therapeutic index. Duloxetine and bupropion are moderate inhibitors of CYP2D6, and sertraline may cause significant inhibition of this isoform, but only at high doses. Citalopram, escitalopram, venlafaxine, mirtazapine, and reboxetine are weak or negligible inhibitors of CYP isozymes in vitro and are less likely than other second-generation antidepressants to interact with co-administered medications.

CONCLUSIONS

Second-generation antidepressants are not equivalent in their potential for pharmacokinetic drug interactions. Although interactions may be predictable in specific circumstances, use of an antidepressant with a more favorable drug-interaction profile may be justified.

Interaction study of the combined use of paroxetine and fosamprenavir-ritonavir in healthy subjects

Human immunodeficiency virus-infected patients have an increased risk for depression. Despite the high potential for drug-drug interactions, limited data on the combined use of antidepressants and antiretrovirals are available. Theoretically, ritonavir-boosted protease inhibitors may inhibit CYP2D6-mediated metabolism of paroxetine. We wanted to determine the effect of fosamprenavir-ritonavir on paroxetine pharmacokinetics and vice versa and to evaluate the safety of the combination. Group A started with 20 mg paroxetine every day for 10 days; after a wash-out period of 16 days, subjects received paroxetine (20 mg every day) plus fosamprenavir-ritonavir (700/100 mg twice a day) from days 28 to 37. Group B received the regimens in reverse order. On days 10 and 37, pharmacokinetic curves were recorded. Twenty-six healthy subjects (18 females, 8 males) were included. Median (range) age and weight were 44.4 (18.2 to 64.3) years and 68.8 (51.0 to 89.4) kg. Three subjects were excluded (two because of adverse events; one for nonadherence). Addition of fosamprenavir-ritonavir to paroxetine resulted in a significant decrease in paroxetine exposure: the geometric mean ratios (90% confidence intervals) of paroxetine plus fosamprenavir-ritonavir to paroxetine alone were 0.45 (0.41 to 0.49) for the area under the concentration-time curve from 0 to 24 h (AUC(0-24)), 0.49 (0.45 to 0.53) for the maximum concentration of the drug in plasma (C(max)), and 0.75 (0.71 to 0.80) for the apparent elimination half-life (t(1/2)). The free fraction of paroxetine showed a median (interquartile range) increase of 30% (18 to 42%) after the addition of fosamprenavir-ritonavir. The AUC(0-12), C(max), C(min), and t(1/2) of amprenavir and ritonavir were similar to those of historical controls. No serious adverse events occurred. Fosamprenavir-ritonavir reduced total paroxetine exposure by 55%. This is partly explained by protein displacement of paroxetine. We think that this interaction is clinically relevant and that titration to a higher dose of paroxetine may be necessary to accomplish the needed antidepressant effect.

Determination of the antidepressant paroxetine and its three main metabolites in human plasma by liquid chromatography with fluorescence detection

A high-performance liquid chromatographic method has been developed for the determination in human plasma of the specific serotonin reuptake inhibitor (SSRI) antidepressant paroxetine and its three main metabolites (M1, M2, M3). Fluorescence detection was used, exciting at lambda = 294 nm and monitoring emission at lambda = 330 nm for paroxetine (lambda(exc) = 280 nm, lambda(em) = 330 nm for M1 and M2; lambda(exc) = 268 nm, lambda(em) = 290 nm for M3). Separation was obtained on a reversed-phase C18 column using a mobile phase composed of 66.7% aqueous phosphate at pH 2.5 and 33.3% acetonitrile. Imipramine (lambda(exc) = 252 nm, lambda(em) = 390 nm) was used as the internal standard. A careful pre-treatment of plasma samples was developed, using solid-phase extraction with C8 cartridges (50 mg, 1 mL). The calibration curves were linear over a working range of 2.5-100 ng mL(-1) for paroxetine and of 5-100 ng mL(-1) for all metabolites. The limit of detection (LOD) was 1.2 ng mL(-1) for PRX and 2.0 ng mL(-1) for the metabolites. The method was applied with success to plasma samples from depressed patients undergoing treatment with paroxetine. Hence, the method seems to be suitable for the therapeutic drug monitoring of paroxetine and its main metabolites in depressed patients' plasma.

Antidepressants and their effect on sleep

Given the relationship between sleep and depression, there is inevitably going to be an effect of antidepressants on sleep. Current evidence suggests that this effect depends on the class of antidepressant used and the dosage. The extent of variation between the effects of antidepressants and sleep may relate to their mechanism of action. This systematic review examines randomised-controlled trials (RCTs) that have reported the effect that antidepressants appear to have on sleep. RCTs are not restricted to depressed populations, since several studies provide useful information about the effects on sleep in other groups. Nevertheless, the distinction is made between those studies because the participant's health may influence the baseline sleep profiles and the effect of the antidepressant. Insomnia is often seen with monoamine oxidase inhibitors (MAOIs), with all tricyclic antidepressants (TCAs) except amitriptyline, and all selective serotonin reuptake inhibitors (SSRIs) with venlafaxine and moclobemide as well. Sedation has been reported with all TCAs except desipramine, with mirtazapine and nefazodone, the TCA-related maprotiline, trazodone and mianserin, and with all MAOIs. REM sleep suppression has been observed with all TCAs except trimipramine, but especially clomipramine, with all MAOIs and SSRIs and with venlafaxine, trazodone and bupropion. However, the effect on sleep varies between compounds within antidepressant classes, differences relating to the amount of sedative or alerting (insomnia) effects, changes to baseline sleep parameters, differences relating to REM sleep, and the degree of sleep-related side effects.

Mirtazapine in combination with amitriptyline: a drug-drug interaction study in healthy subjects

OBJECTIVE

To assess the steady-state pharmacokinetics of mirtazapine (30 mg/day orally) and amitriptyline (75 mg/day orally) during combined administration compared with that of either drug administered alone. To evaluate the tolerability and effects on psychometric tests of acute and subchronic administration of both drugs combined and alone.

METHODS

In a single-blind, three-way cross-over study, 24 (12 male and 12 female) healthy subjects were randomly assigned to six different sequences of three 9-day treatments, i.e. racemic mirtazapine (30 mg/day), amitriptyline (75 mg/day) or the combination of these drugs. To control for acute pharmacodynamic assessments, during the first treatment period, a placebo group (n = 8; 4 females and 4 males) was added. Serial blood samples were drawn for plasma level measurements that were subsequently subjected to pharmacokinetic analysis. Psychometric tests assessed attentional performance, and a computer-assisted telephone questionnaire assessed self-ratings of drowsiness/alertness and sleep quality.

RESULTS

Amitriptyline increased the C(max) of mirtazapine (+ 36%, p < 0.05) in male subjects only. Mirtazapine altered the C(max) of amitriptyline in both male (+ 23%, p < 0.05) and female (- 23%, p < 0.05) subjects. No changes were observed for other pharmacokinetic parameters. Metabolite parameters were not affected. Changes in parent compound levels mainly resulted from effects on absorption. The psychometric test results did not reveal significant changes between combined and single drug treatments. The telephone registrations of VAMRS and LSEQ did not show clinically relevant differences between the active treatments.

CONCLUSION

Combined administration of mirtazapine (30 mg/day) and amitriptyline (75 mg/day) alters the pharmacokinetics of either compound to a minor extent. Adding one drug to the other and substituting one drug by the other had no major effects on tolerability. Nevertheless, caution is warranted when combining amitriptyline and mirtazapine.